The present invention relates to the art of operating parameter optimization. It finds particular application in conjunction with optimizing scan parameters for a magnetic resonance imaging apparatus and will be described with particular reference thereto. It is to be appreciated, however, that the present invention is also applicable to the otpimization of scan parameters in conjunction with computerized tomographic scanning apparatus, magnetic resonance spectrometers, other non-invasive medical imaging and diagnostic apparatus, and the like.
Heretofore, the operating parameters of magnetic resonance imaging apparatus has commonly been set based on the experience of the operator. These operating parameters included selection of the imaging sequence, scan times, slice thickness, number of views to be summed in each image, and numerous other operating parameters as are conventional in the art. As might be expected, the suitability of a resultant image for the intended diagnostic purposes varied widely from operator to operator.
Operator educational systems helped the operator to understand the significance of various operating parameters. The education helped to obtain greater consistency of results from operator to operator. One such education system incorporated image simulation by mathematical modeling of individual ones of the performance indices, such as contrast, signal-to-noise, and, motion rejection. From this simulation, the operator came to understand more precisely the effect on the ultimate image that various adjustments of the twenty or so scan parameters on the intitial protocol would achieve.
Another educational tool involved a retrospective image synthezization. Three scans were taken through the same slice or region of a patient, each with different scan parameters. In one scan, the scan parameters were set to emphasize proton density; in the second scan, the scan parameters were set to emphasize T1 relaxation time; and, in the third scan, the parameters were set to emphasize T2 relaxation time. The images from these three scans were electronically mixed with different weightings to illustrate the effects of adjustments to the various available scan parameters. The differently weighted electronically mixed images each emphasized or obscured different lesions, tumors, tissues, disease processes, and the like to different degrees. In this manner, the operator was trained to select the most characteristic scan parameters for the medical diagnostic purpose at hand. This retrospective system had the drawbacks of relying on operator skill. Moreover, the educational techniques tended to focus on a single scan parameter without educating the operator on how the various scan parameters interacted synergistically to affect the final image.
In another retrospective technique, three images were taken of the scan plane of a patient being diagnosed, each image emphasizing one of proton density, T1 relaxation time, and T2 relaxation time. After the scanning was complete and the patient had left, the three images were mixed with various weightings. The various mixings attempted to optimize a performance variable or otherwise optimize the characteristics of the resultant image for the selected diagnosis. This technique was again inefficient. Extra scanning time was required to collect the multiple scans. Further, the flexibility was limited to modifying the image reconstruction with previously collected data. The three images were each taken with a different but fixed protocol of scan parameters, none of which were commonly optimal for the diagnosis in question.
The prior art suffers from several drawbacks including an inability to individualize the examination to a patient being imaged. Rather, it must rely on historical data or learning. Another drawback is a relative inflexibility in the potential combinations of scan parameters. Commonly, machine adjustability is limited in order to achieve simplicity of operation. Further, operators are rarely capable of appreciating the full significance of adjustments to the twenty or so scan parameters that might be adjusted.
The present invention provides a new and improved automatic optimization of all scan parameters for the nature of the diagnosis to be performed with the resultant image.